Publications by authors named "Radu Grovu"

Patients with renal artery stenosis (RAS) who fail medical management may be evaluated for Percutaneous transluminal renal artery angioplasty/stenting (PTRA/S). Comorbidities increasing the risk of complications following PTRA have not been explored well. Patients undergoing PTRA/S for RAS were sampled using National Inpatient Sample (NIS) Database.

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Background: Acute heart failure in patients with prosthetic heart valves is a complex problem with clinical and therapeutic challenges. Systemic sclerosis is a chronic autoimmune disease frequently associated with valvular abnormalities. The association between systemic sclerosis and acute heart failure in patients with prosthetic heart valves remains understudied.

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Background: Although transcatheter aortic valve replacement has emerged as an alternative to surgical aortic valve replacement, it requires extensive healthcare resources, and optimal length of hospital stay has become increasingly important. This study was conducted to assess the potential of novel machine learning models (artificial neural network and eXtreme Gradient Boost) in predicting optimal hospital discharge following transcatheter aortic valve replacement.

Aim: To determine whether artificial neural network and eXtreme Gradient Boost models can be used to accurately predict optimal discharge following transcatheter aortic valve replacement.

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There is a paucity of data on the cardiovascular implications of monoclonal gammopathy of undetermined significance, especially among hospitalized patients. Our study aimed to investigate the association between MGUS and cardiovascular outcomes in a hospital setting using the National Inpatient Sample database. MGUS patients were sampled using ICD-10 codes.

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Cannabis use is becoming increasingly prevalent worldwide, yet the full spectrum of its effects largely remain unknown. Although cannabis have immunomodulatory properties, there remains a significant gap in our understanding of the potential impact of marijuana use on COVID-19 outcomes. The purpose of this study is to evaluate the effect of chronic cannabis use on severe COVID-19.

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Background: Device-related infective endocarditis (IE) is associated with high mortality, resulting in a growing emphasis on identifying and managing comorbidities that increase the risk of IE in these patients. Psoriasis is increasingly being recognized as having multiple cardiovascular manifestations. However, little is known about the impact of psoriasis on IE risk in patients with permanent pacemakers (PPM).

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Background: There are no studies currently in the literature that assesses complications following revision total shoulder arthroplasty (TSA) in patients with varying severity of anemia. The purpose of this study was to determine the impact of preoperative anemia severity on postoperative complications following revision TSA.

Methods: Patients undergoing revision TSA from 2013 to 2019 were queried in a national database.

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Background: With the widespread use of permanent pacemakers (PPM), and increased mortality associated with pacemaker endocarditis, it is essential to evaluate comorbidities that could potentially increase the risk of infective endocarditis (IE). Heart failure (HF), a common comorbidity, has not been well studied as an independent risk factor for development of IE in individuals with PPM.

Methods: The US National Inpatient Sample database was used to sample individuals with PPM.

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Background: Cardiovascular disease (CVD) is the leading cause of mortality in kidney transplant (KT) patients. The perceived risk of contrast-induced nephropathy (CIN) may create a reluctance to perform coronary angiography in patients presenting with non-ST segment elevation myocardial infarction (NSTEMI).

Methods: National Inpatient Sample (NIS) Database was used to sample individuals presenting with NSTEMI.

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Primary hyperthyroidism (PHPT) is a relatively uncommon disease and leads to increased calcium levels. Ionized calcium, known as clotting Factor IV, may lead to overt coagulation cascade activation, increasing the risk of venous thromboembolism (VTE). National Inpatient Sample Database was used to sample individuals with primary hyperparathyroidism, and baseline demographics and comorbidities were collected using ICD-10 codes.

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Article Synopsis
  • This study investigates the use of machine learning (ML) to predict hospital stays for patients with severe systemic lupus erythematosus (SLE), focusing on factors that can extend hospitalization.
  • Data from 5,831 SLE patients was analyzed using various ML models, with XGBoost emerging as the most effective, showing high accuracy and strong performance metrics.
  • Key factors impacting length of stay included the need for central lines, acute dialysis, and acute renal failure, indicating that ML could improve care by identifying at-risk patients.
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Background: Cognitive dysfunction is a core transdiagnostic domain of Major Depressive Disorder (MDD) and is a principal determinant of functional recovery. However, it has been insufficiently targeted within the current therapeutic framework for MDD.

Objective: To highlight these unmet cognitive needs in MDD.

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